Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Rademacher and gaussian complexities: risk bounds and structural results
The Journal of Machine Learning Research
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Semi-Supervised Learning on Riemannian Manifolds
Machine Learning
Support Vector Machine Soft Margin Classifiers: Error Analysis
The Journal of Machine Learning Research
Learning the Kernel Function via Regularization
The Journal of Machine Learning Research
Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied & Computational Mathematics)
Multi-kernel regularized classifiers
Journal of Complexity
Information Sciences: an International Journal
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
The Journal of Machine Learning Research
Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification
Information Sciences: an International Journal
On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning
The Journal of Machine Learning Research
Clustering high dimensional data: A graph-based relaxed optimization approach
Information Sciences: an International Journal
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Graph-Based Semi-Supervised Learning and Spectral Kernel Design
IEEE Transactions on Information Theory
Semisupervised multicategory classification with imperfect model
IEEE Transactions on Neural Networks
Semi-supervised learning based on high density region estimation
Neural Networks
Personalized mode transductive spanning SVM classification tree
Information Sciences: an International Journal
A nonparametric classification method based on K-associated graphs
Information Sciences: an International Journal
Classification and annotation in social corpora using multiple relations
Proceedings of the 20th ACM international conference on Information and knowledge management
Information Sciences: an International Journal
Semi-supervised change detection using modified self-organizing feature map neural network
Applied Soft Computing
Detecting network communities using regularized spectral clustering algorithm
Artificial Intelligence Review
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In this paper, we investigate the generalization performance of the multi-graph regularized semi-supervised classification algorithm associated with the hinge loss. We provide estimates for the excess misclassification error of multi-graph regularized classifiers and show the relations between the generalization performance and the structural invariants of data graphs. Experiments performed on real database demonstrate the effectiveness of our theoretical analysis.